What Is Demand Forecasting? (With Types And Benefits)

By Indeed Editorial Team

Published 8 August 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Businesses use various techniques to predict customer demand for products and services over a fixed period. Demand forecasting, also known as sales forecasting, is a popular technique that businesses employ to gauge customer demand using historical data and other information. Learning about demand forecasting can help you understand how companies use this process for business planning, budgeting, inventory stocking and goal setting. In this article, we answer the question, 'What is demand forecasting?', learn its various types, find out how it can benefit businesses and go through some tips to improve demand forecasting.

What Is Demand Forecasting?

The answer to, 'What is demand forecasting?' is that it is a process that businesses utilise to understand and predict customer demand over a period. This helps them make informed decisions about supply chain operations, inventory stocking, capacity planning, cash flow and profit margins. They use various demand forecasting methods, such as:

  • Trend projection: Trend projection uses historical data to project future sales. It is important to remove outliers, such as sudden spikes in sales and historical anomalies, before opting for this method.

  • Market research: Market research uses data from customer surveys to provide businesses with valuable information. It helps cluster customers based on their purchasing habits, demographic, geographic and psychographic variables.

  • Delphi method: It involves sending several questionnaires to an expert panel over several rounds to generate forecasts. The primary objective of this technique is to arrive at a group consensus which can provide unified expert opinion.

  • Sales force composite: This method uses data from the sales groups to predict future demand for a product or a service. The sales team provides data such as customer behaviour, product trends, competitors' products and pricing strategies and customer feedback.

  • Econometric technique: This technique combines sales data with external economic factors to build a mathematical model that can accurately predict future customer demand. The external factors can include regulations and policies, technology, macroeconomic conditions and geopolitical scenarios.

Related: What Are Price Monitoring Tools? (Definition And Examples)

Benefits Of Demand Forecasting

Here are some benefits of demand forecasting:

Increased supply chain efficiency

Using demand forecasting, businesses can predict the demand for their products over a period. By analysing sales and seasonal trends, they can streamline their production process, warehousing and shipping. This helps improve the supply chain efficiency and enables them to minimise logistics costs and maximise profits. For example, if a business determines that there is likely to be a surge in the demand for a product before the festive season, it can contact multiple suppliers to ensure that they have enough supply to meet the customers' demands.

Related: What Is A Supply Chain? (With Supply Chain Types And Steps)

Efficient budgeting

Demand forecasting can help businesses create cash flow and manufacturing budgets. This enables them to allocate budgets based on market trends, customer demand and fluctuating income. For example, a small company can use demand forecasting to determine slow and busy sales periods and plan promotions and social media campaigns accordingly.

Related: What Is Capital Budgeting? (Definition And Methods)

Improved cash flow management

Cash flow is the amount of money that flows in and out of a business during a period. Poor cash flow management results in additional debts, inability to pay suppliers on time or make new purchases and loss of contracts. Demand forecasting allows businesses to gain insight into their products' varying demands, allowing them to manage their cash flow more effectively.

Related: Format Of A Cash Flow Statement (With Methods And Examples)

7 Types Of Demand Forecasting

The seven types of demand forecasting include:

1. Passive demand forecasting

Passive demand forecasting is a simple technique that involves predicting future customer demand based on historical data. The historical data may include:

  • Identity data: Identity data includes a customer's name, contact information, demographics and links to social media accounts.

  • Descriptive data: Descriptive data includes additional details, such as a customer's marital status, career details and educational information.

  • Behavioural data: Behavioural data includes data on past purchases, customer interactions with a business, social engagement and product usage.

  • Attitudinal data: Attitudinal data is information about customers' thoughts, feelings and opinions about a product, brand or experience.

This is an ideal strategy for companies that focus on sustainability and prioritise stability over growth or expansion.

Related: What Is A Marketing Manager? Definition, Roles And Skills

2. Active demand forecasting

This is an ideal strategy for companies that prioritise growth and diversification over stability and sustainability. This technique focuses on various factors besides sales data, such as marketing campaign data, competitors' activities, external market conditions and trends. Businesses that are looking to change their marketing tactics or focus on expansion can benefit from employing this method.

Related: What Is Strategic Marketing? (With Benefits And Tips)

3. Macro-level demand forecasting

At a macro-level, demand forecasting examines external factors, including economic conditions, competition and consumer trends. This helps businesses identify opportunities for product or service expansion, determine financial risks and procure raw materials in advance. Demand forecasting at the macro level is based on national income or aggregate expenditures.

Related: Macroeconomics: A Complete Guide (With History And Scope)

4. Industry-level demand forecasting

Industry-level demand forecasting measures the overall demand for the products of a particular industry. This can include industries at the regional or national level. An industry, trade association or a group of companies may undertake these forecasts.

Related: Outbound Marketing Vs. Inbound Marketing: Pros And Cons

5. Firm-level demand forecasting

This involves predicting the demand for products offered by a particular company. Companies can develop marketing strategies based on this information. Businesses experiencing rapid growth prefer using industry-level demand forecasting, whereas those with stable growth benefit from using firm-level demand forecasting.

Related: What Is Internet Marketing? (Definition And Types)

6. Short-term demand forecasting

This type of forecasting predicts customer demand for the period of three months to one year. The short-term demand forecasting method uses real-time sales data to adjust projections of customer demand. This can help businesses achieve short-term goals, such as preparing suitable sales policies to improve sales or preparing inventory based on demand.

Related: Top 20 Careers In Marketing: Average Salary And Requirements

7. Long-term demand forecasting

Businesses use long-term forecasts for periods exceeding one year. It helps them identify annual patterns, seasonality in sales and production capacity. Using long-term demand forecasting, businesses can devise long-term strategies to increase their market share, acquire other businesses, grow their customer base and improve production processes.

Tips To Improve Demand Forecasting

Here are tips to improve demand forecasting:

Focus on data analytics

It is essential for businesses to choose data that is accurate, complete, reliable and relevant to build an effective forecasting system. They can also include other factors, such as promotions and sales, that could affect the number of goods sold. By processing the data and converting it into an easy-to-understand form, analysts can create dashboards that are clean, interactive, easy to use and provide valuable insights.

Measure data accuracy

Measuring demand forecasting accuracy is best achieved by comparing forecasts with the actual demand received. This help businesses determine the accuracy of their forecasting techniques. In case there is an underestimation or overestimation of demand, they can focus on improving their methodologies to obtain an accurate forecast.

Focus on order fulfilment

Sometimes businesses may face a shortage of goods due to various reasons, such as underestimating customer demand, delays in supply and incorrect inventory data. This may cause a loss in revenue, impact customer experience and deplete the brand's value. To avoid this, businesses may avail the services of third-party suppliers and vendors to fulfil the customer's needs. This may result in incorrect data entry and affect demand forecasting. It is essential for businesses to include this data when using predictive analysis.

Manage surges in demand

Many businesses may notice spikes in sales data. This can happen because of various reasons, such as abnormalities in data or unusual demand for products during a specific period. Outliers in data may skew the inventory planning. It is necessary for businesses to study these outliers and classify them as one-time occurrences or a trend. This can help them manage their demand forecast and improve business processes.

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